nCircle Tech | Blogs | Understanding the Implications of Machine Learning for the Construction Industry
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AI, Machine Learning, and Deep Learning are relatively newer concepts that demand awareness, discussions, and brainstorming. This process becomes even more crucial when it comes to the construction industry, as these are new-age technologies and the industry players are yet to integrate their traditional working methods with the advanced technologies. These technologies hold great opportunities in terms of cost reduction, efficiency, and higher productivity. This is especially true during and post COVID19. 

However, construction and manufacturing businesses can understand the use cases of these advanced systems only after understanding their definition, features, capacities, benefits, and of course the future.

In the end, a smart business will always look for a sustainable solution that can reduce stress, cut down expenses, and add to productivity.

Though a piece of article is definitely not enough to discuss the applications and impact of Machine Learning, AI, and Deep Learning in the construction industry; the content will surely help in getting a brief idea of the advanced technologies and their utility

Let us dig deeper :

Definition of AI, Machine Learning, and Deep Learning.

  • Artificial Intelligence mimics natural human intelligence, replicating the way the human brain functions, thinks, and works. The technology is in progress.
  • Machine Learning (ML) is quite what the name suggests. The technology teaches computer devices to understand patterns, commands, and figure things out on their own. It allows supervised and unsupervised learning.
  • For example, ML algorithms can be “trained” to find spam emails by introducing it to the large data of emails tagged as spam and no-spam. The algorithm will find the similarities and differences between these emails and ‘learn’ define the patterns and identify the spam emails from every provided data, on its own.
  • While ML can be looked at as a subset of AI, Deep Learning is a subset of Machine Learning that is developed to help computer devices in solving complicated issues.
  • In case, the things yet not clear, let us understand the technologies in-depth and find the difference Between AI, Machine Learning, and Deep Learning.

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What Is Machine Learning in Construction?

Any shift of perspective or strategic shifts do not happen overnight, but the construction industry has all the potential and scope to actively adopt new technologies. 

As per the NBS (National Building Specification) Construction Technology Report 2019, around 90% of the businesses agree that adopting digitization will transform the way they work.

Machine Learning in AEC can be a savior

A typical construction project has hundreds of issues.  Construction manager deals with a number of on-going tasks, a change of orders, constant demand for data, and its continuous flow. 

Now imagine an intelligent technological assistant gathering a huge amount of data, processing it, grading it, and sharing it with every concerned professional and department taking care of the construction project. Remember, all of this is being done recurrently, within a time much lesser than a human mind would require.

Some social media platforms use AI too. When one posts a photograph on the platform and the system automatically suggests accurate names (to tag) of the people captured in the photograph, there is an intelligent system working in the background!

The same technology can be used on the construction site to assist in workers’ attendance, checking safety measures, etc. The supervisor can know if the worker is properly using PPE or otherwise. If any of the safety measures have been compromised, the photograph of the worker or the place can be tagged and shared with the supervisor immediately.

The manager can feed the Machine Learning algorithm deployed on the construction site with all the data of the workers operating on the construction project.

In case, any worker or professional is not seen in the work area at the assigned time, their absence can be informed to the supervisor and related measures can be taken. Construction progress of the project or specific parts of the project can be tracked with ML.

Companies Looking For Higher Utility Value

Talking of ML applications and utility, it is completely acceptable and expected if the construction business is looking for higher utility value when it comes to the deployment of any technology in the business operations. Hence, here are some more ways in which businesses can expect AI, Deep Learning and ML to work for them:

  • Identification of work issues such as lack of material, and missing inventory.
  • Flaws in the operations (if any) such as communication gap or time gap.
  • Handling managerial tasks like tagging and organizing documents.
  • On-site responsibilities like, running machines, drones, developing designs, etc.
  • Identifying high-risk subcontractors after analyzing their past records, real-time performance, and other factors. Just another way of ensuring on-site safety and quality construction!
  • Integrating Machine Learning in CAD and BIM software for informed & sustainable designs.
  • Utilizing Machine Learning for cost efficiency, cost estimation, labor management, and smart work.
  • Robotics and LIDAR technology in amalgamation with AI to develop a realistic imitation or miniature of the construction site.

Let Us See More About Machine Learning For Architecture and Construction Companies:

Machine Learning and AI have been in the market for a few years and are used by innovative construction companies in their own way. Some of the present-day importance and applications of these technologies are

Risk Management:

One of the benefits of integrating ML-based solutions in AEC and manufacturing is effective risk management. Risk management is said to be performed smoothly if all the stages are coherent and do not share time-lag or do not lose data. The four stages being:

  • Risk Identification, 
  • Risk Assessment,
  • Risk Response &
  • Risk Monitoring and Control.

Machine Learning connects these stages and performs them all in a flow.

Dealing With Uncertainties:

In the construction business, right from lack of raw material, dull construction designs, environmental hurdles to workers’ safety, an emergency can show up in any operational area and the on-site/off-site management has to be ready to deal with it. 

However, what if the business implements advanced technologies that have all the required data from the past & present to predict future happenings? And what if they can also notify the concerned team to take the needful measures, in real-time?

AI and Machine Learning can monitor and track inventories, workers’ performance, tentative duration of project completion, compatibility of the safety measures, etc. ML algorithms can monitor and report incidences happening at the construction site for better control over the project.

Smoother & Speeded Construction Process

At construction sites, what are the chances of things going wrong? There is every chance! In the construction industry, there is always a scope for error. Multiple activities are being conducted simultaneously for faster completion of the project, sometimes cresting complicated work environments and errors. Based on the data provided, ML-based solutions in AEC and manufacturing would help in prediction, and possible recovery solutions/actions too. AI and Deep Learning can also save businesses from repetitive tasks.

To name a few of the many smart ML powered solutions that accomplish more complex tasks with ease and in no time is Scan to BIM where you can identify BIM objects from scanned point cloud data. No manual mapping required with the scanned data once your engineer is back to office. Let’s take it one notch higher now with the BIM Voice Assistant – a voice UI assistance based on NLP for commands frequently used by design reviewers in the CAD and BIM industry. This will pick the features in the drawing without manual multiple clicks and your novice team can work on the software too. A further deep dive will lead us to ML powered Automatic Feature Recognition in model plans and OCR for text extraction from complex construction plans, and so on. No manual data transfer, no human errors, no time gap, and no manual supervision! These are a few of the many examples of how smart and robust this technology can get to assist you in your construction projects.

Intelligence Demanding Tasks Become Easier:

Some tasks where higher intelligence level and speed is required can be done through ML-based software for faster operations, like project management, architecture & design, engineering, etc. The software would be able to process the data and assist the manager in planning, architecture, design, prioritizing the work, etc.

Deciding the Profit Margin:

At the moment, most of the businesses decide their profit margins based on past data, market rate, judgments, or uniform rates. In short, the margin prediction is hardly accurate and businesses start witnessing a reduction in the profit margin as the project starts progressing. Hence, a huge gap between expected and actual profit margins.

Most of the businesses hold past projects’ data for the BIM. This data gets stored in relational, XLS form. Not to mention, this data has every detail of when and how the firm’s profit margins changed. Machine Learning and Deep Learning in CAD plugins / BIM plugins come handy to identify the connection between project attributes and profit margins.

Conclusion:

Large-sized and commercial construction projects are actively deploying AI, Machine Learning, and Deep Learning solutions to reduce the risks, add to productivity, and to automate decision making. Right now, the focus is to use advanced technologies to complement human efforts, not to replace it.

At present, it can be hard for medium-sized or small-sized businesses to leverage the technology to the fullest, but the use cases of the technologies are reflecting the positive results and hence attracting many businesses to go for the same.

Construction businesses that wish to build a sustainable brand in the market with the utmost productivity at disposal, fueling your organization with advanced technological support can work wonders.

If you wish to know more about ML/AI solutions that can help resolve an industry challenge you are facing with your construction business operations; we will be glad to connect and reach out to you through contact us

nCircle Tech (inCorporated in 2012) empowers passionate innovators to create impactful 3D visualization software for desktop, mobile, and cloud. Our domain expertise in CAD-BIM customization drives automation with the ability to integrate advanced technologies like AI/ML and VR/AR; empowers our clients to reduce time to market and meet business goals. nCircle has a proven track record of technology consulting and advisory services for the AEC and Manufacturing industry across the globe. Our team of dedicated engineers, partner ecosystem and industry veterans are on a mission to redefine how you design and visualize.

Author : nCircle Tech

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